Boundary layer depth

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Boundary layer depth#

%load_ext autoreload
%autoreload 2

%%capture 
# comment above line to see details about the run(s) displayed
from misc import *
from mom6_tools.m6plot import myStats, annotateStats
import cartopy.crs as ccrs
import cartopy.feature
import intake
%matplotlib inline

Monthly#

for path, case, i in zip(ocn_path, casename, range(len(casename))):
  ds =  xr.open_dataset(path+case+'_BLD_monthly_clima.nc')
  g = ds.oml.plot(x="longitude", y="latitude", col='month', 
                col_wrap=3,
                robust=True,
                figsize=(14,12),
                cmap='nipy_spectral',
                vmin=0., vmax=1000.,
                cbar_kwargs={"orientation": "horizontal", "pad": 0.05},
               )
  # Add a suptitle
  g.fig.suptitle('Run {}, mean between {} to {}'.format(label[i], start_date, end_date), fontsize=16, y=1.02);
_images/5e6fae48df3d32b33074c9958863846494106d4b1ae80d40ff7c7d6b62bed5d1.png

Winter#

for path, case, i in zip(ocn_path, casename, range(len(casename))):
  ds =  xr.open_dataset(path+case+'_BLD_winter.nc')
  winter = np.ma.masked_invalid(ds.BLD_winter.values)

  try:
    area= grd[i].area_t
  except:
    area= grd[i].areacello
      
  # winter
  plot_map(winter, area, grd[i], label[i], 
           vmin=0, vmax=1500, suptitle="Mean BLD Winter, JAS(SH), JFM(NH)",
           cmap='nipy_spectral')
_images/ee705512c093e097fe07bcffeb9398f55b2d38ab91ed84f536e1d19c52196dbb.png

Summer#

for path, case, i in zip(ocn_path, casename, range(len(casename))):
  ds =  xr.open_dataset(path+case+'_BLD_summer.nc')
  summer = np.ma.masked_invalid(ds.BLD_summer.values)

  try:
    area= grd[i].area_t
  except:
    area= grd[i].areacello
      
  # summer
  plot_map(summer, area, grd[i], label[i], 
           vmin=0, vmax=200, suptitle="Mean BLD Summer, JFM(SH), JAS(NH)", 
           nh='JAS', sh='JFM', cmap='nipy_spectral')
_images/9fea7b80ccc5a27a3b361ef09bd2c6fa026ad6e491d69187d2a288c1d0769447.png
Contents